1

I heard standard evaluation is not recommended in dplyr, and we can do similar thing with enquo() and quo().

My original code (simplified) is

my_function <- function(data, x="OriginalX", y="OriginalY"){
  data %>%
     mutate_(CopyX = x, CopyY = y)
}

and it works.

I tried following code

my_function <- function(data, x="OriginalX", y="OriginalY"){
  qx <- enquo(x)
  qy <- enquo(y)
  data %>%
     mutate(CopyX = (!!qx), CopyY = (!!qy))
}

Why it does not work? And should we keep using standard evaluation?

4

1 回答 1

4

The idea behind tidyeval is specifically that you don't need to put your column name between "". So this should work:

my_function <- function(data, x= OriginalX , y= OriginalY ){
  qx <- enquo(x)
  qy <- enquo(y)
  data %>%
    mutate(CopyX = !!qx,
           CopyY = !!qy)
}

Note that the !!qx and !!qy don't need to be between parenthesis

my_function(iris, Sepal.Length, Species) %>%
  head()
  Sepal.Length Sepal.Width Petal.Length Petal.Width Species CopyX  CopyY
1          5.1         3.5          1.4         0.2  setosa   5.1 setosa
2          4.9         3.0          1.4         0.2  setosa   4.9 setosa
3          4.7         3.2          1.3         0.2  setosa   4.7 setosa
4          4.6         3.1          1.5         0.2  setosa   4.6 setosa
5          5.0         3.6          1.4         0.2  setosa   5.0 setosa
6          5.4         3.9          1.7         0.4  setosa   5.4 setosa

If you need to use strings in the function parameters, you can use the ensym function to convert them:

my_function <- function(data, x= "OriginalX" , y= "OriginalY" ){
  qx <- ensym(x)
  qy <- ensym(y)
  data %>%
    mutate(CopyX = !!qx,
           CopyY = !!qy)
}

my_function(iris, "Sepal.Length", "Species") %>%
  head()
  Sepal.Length Sepal.Width Petal.Length Petal.Width Species CopyX  CopyY
1          5.1         3.5          1.4         0.2  setosa   5.1 setosa
2          4.9         3.0          1.4         0.2  setosa   4.9 setosa
3          4.7         3.2          1.3         0.2  setosa   4.7 setosa
4          4.6         3.1          1.5         0.2  setosa   4.6 setosa
5          5.0         3.6          1.4         0.2  setosa   5.0 setosa
6          5.4         3.9          1.7         0.4  setosa   5.4 setosa
于 2018-07-11T04:58:44.153 回答